Merge pull request #605 from vpisarev:c2cpp_calib3d_stereo
This commit is contained in:
commit
816adcfdac
@ -669,18 +669,32 @@ CV_EXPORTS_W void triangulatePoints( InputArray projMatr1, InputArray projMatr2,
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CV_EXPORTS_W void correctMatches( InputArray F, InputArray points1, InputArray points2,
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OutputArray newPoints1, OutputArray newPoints2 );
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class CV_EXPORTS_W StereoMatcher : public Algorithm
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{
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public:
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CV_WRAP virtual void compute( InputArray left, InputArray right,
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OutputArray disparity ) = 0;
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};
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enum { STEREO_DISP_SCALE=16, STEREO_PREFILTER_NORMALIZED_RESPONSE = 0, STEREO_PREFILTER_XSOBEL = 1 };
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CV_EXPORTS Ptr<StereoMatcher> createStereoBM(int numDisparities=0, int SADWindowSize=21);
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CV_EXPORTS Ptr<StereoMatcher> createStereoSGBM(int minDisparity, int numDisparities, int SADWindowSize,
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int P1=0, int P2=0, int disp12MaxDiff=0,
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int preFilterCap=0, int uniquenessRatio=0,
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int speckleWindowSize=0, int speckleRange=0,
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bool fullDP=false);
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template<> CV_EXPORTS void Ptr<CvStereoBMState>::delete_obj();
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/*!
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Block Matching Stereo Correspondence Algorithm
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The class implements BM stereo correspondence algorithm by K. Konolige.
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*/
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// to be moved to "compat" module
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class CV_EXPORTS_W StereoBM
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{
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public:
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enum { PREFILTER_NORMALIZED_RESPONSE = 0, PREFILTER_XSOBEL = 1,
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BASIC_PRESET=0, FISH_EYE_PRESET=1, NARROW_PRESET=2 };
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BASIC_PRESET=0, FISH_EYE_PRESET=1, NARROW_PRESET=2 };
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//! the default constructor
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CV_WRAP StereoBM();
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@ -697,11 +711,7 @@ public:
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};
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/*!
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Semi-Global Block Matching Stereo Correspondence Algorithm
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The class implements the original SGBM stereo correspondence algorithm by H. Hirschmuller and some its modification.
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*/
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// to be moved to "compat" module
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class CV_EXPORTS_W StereoSGBM
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{
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public:
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@ -736,7 +746,7 @@ public:
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CV_PROP_RW bool fullDP;
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protected:
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Mat buffer;
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Ptr<StereoMatcher> sm;
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};
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//! filters off speckles (small regions of incorrectly computed disparity)
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216
modules/calib3d/src/compat_stereo.cpp
Normal file
216
modules/calib3d/src/compat_stereo.cpp
Normal file
@ -0,0 +1,216 @@
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//M*//////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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CvStereoBMState* cvCreateStereoBMState( int /*preset*/, int numberOfDisparities )
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{
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CvStereoBMState* state = (CvStereoBMState*)cvAlloc( sizeof(*state) );
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if( !state )
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return 0;
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state->preFilterType = CV_STEREO_BM_XSOBEL; //CV_STEREO_BM_NORMALIZED_RESPONSE;
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state->preFilterSize = 9;
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state->preFilterCap = 31;
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state->SADWindowSize = 15;
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state->minDisparity = 0;
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state->numberOfDisparities = numberOfDisparities > 0 ? numberOfDisparities : 64;
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state->textureThreshold = 10;
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state->uniquenessRatio = 15;
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state->speckleRange = state->speckleWindowSize = 0;
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state->trySmallerWindows = 0;
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state->roi1 = state->roi2 = cvRect(0,0,0,0);
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state->disp12MaxDiff = -1;
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state->preFilteredImg0 = state->preFilteredImg1 = state->slidingSumBuf =
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state->disp = state->cost = 0;
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return state;
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}
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void cvReleaseStereoBMState( CvStereoBMState** state )
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{
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if( !state )
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CV_Error( CV_StsNullPtr, "" );
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if( !*state )
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return;
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cvReleaseMat( &(*state)->preFilteredImg0 );
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cvReleaseMat( &(*state)->preFilteredImg1 );
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cvReleaseMat( &(*state)->slidingSumBuf );
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cvReleaseMat( &(*state)->disp );
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cvReleaseMat( &(*state)->cost );
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cvFree( state );
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}
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template<> void cv::Ptr<CvStereoBMState>::delete_obj()
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{ cvReleaseStereoBMState(&obj); }
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void cvFindStereoCorrespondenceBM( const CvArr* leftarr, const CvArr* rightarr,
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CvArr* disparr, CvStereoBMState* state )
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{
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cv::Mat left = cv::cvarrToMat(leftarr), right = cv::cvarrToMat(rightarr);
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const cv::Mat disp = cv::cvarrToMat(disparr);
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CV_Assert( state != 0 );
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cv::Ptr<cv::StereoMatcher> sm = cv::createStereoBM(state->numberOfDisparities,
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state->SADWindowSize);
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sm->set("preFilterType", state->preFilterType);
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sm->set("preFilterSize", state->preFilterSize);
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sm->set("preFilterCap", state->preFilterCap);
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sm->set("SADWindowSize", state->SADWindowSize);
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sm->set("numDisparities", state->numberOfDisparities > 0 ? state->numberOfDisparities : 64);
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sm->set("textureThreshold", state->textureThreshold);
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sm->set("uniquenessRatio", state->uniquenessRatio);
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sm->set("speckleRange", state->speckleRange);
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sm->set("speckleWindowSize", state->speckleWindowSize);
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sm->set("disp12MaxDiff", state->disp12MaxDiff);
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sm->compute(left, right, disp);
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}
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CvRect cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity,
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int numberOfDisparities, int SADWindowSize )
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{
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return (CvRect)cv::getValidDisparityROI( roi1, roi2, minDisparity,
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numberOfDisparities, SADWindowSize );
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}
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void cvValidateDisparity( CvArr* _disp, const CvArr* _cost, int minDisparity,
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int numberOfDisparities, int disp12MaxDiff )
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{
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cv::Mat disp = cv::cvarrToMat(_disp), cost = cv::cvarrToMat(_cost);
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cv::validateDisparity( disp, cost, minDisparity, numberOfDisparities, disp12MaxDiff );
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}
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namespace cv
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{
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StereoBM::StereoBM()
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{ init(BASIC_PRESET); }
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StereoBM::StereoBM(int _preset, int _ndisparities, int _SADWindowSize)
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{ init(_preset, _ndisparities, _SADWindowSize); }
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void StereoBM::init(int _preset, int _ndisparities, int _SADWindowSize)
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{
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state = cvCreateStereoBMState(_preset, _ndisparities);
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state->SADWindowSize = _SADWindowSize;
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}
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void StereoBM::operator()( InputArray _left, InputArray _right,
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OutputArray _disparity, int disptype )
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{
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Mat left = _left.getMat(), right = _right.getMat();
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CV_Assert( disptype == CV_16S || disptype == CV_32F );
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_disparity.create(left.size(), disptype);
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Mat disp = _disparity.getMat();
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CvMat left_c = left, right_c = right, disp_c = disp;
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cvFindStereoCorrespondenceBM(&left_c, &right_c, &disp_c, state);
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}
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StereoSGBM::StereoSGBM()
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{
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minDisparity = numberOfDisparities = 0;
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SADWindowSize = 0;
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P1 = P2 = 0;
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disp12MaxDiff = 0;
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preFilterCap = 0;
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uniquenessRatio = 0;
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speckleWindowSize = 0;
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speckleRange = 0;
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fullDP = false;
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sm = createStereoSGBM(0, 0, 0);
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}
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StereoSGBM::StereoSGBM( int _minDisparity, int _numDisparities, int _SADWindowSize,
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int _P1, int _P2, int _disp12MaxDiff, int _preFilterCap,
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int _uniquenessRatio, int _speckleWindowSize, int _speckleRange,
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bool _fullDP )
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{
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minDisparity = _minDisparity;
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numberOfDisparities = _numDisparities;
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SADWindowSize = _SADWindowSize;
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P1 = _P1;
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P2 = _P2;
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disp12MaxDiff = _disp12MaxDiff;
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preFilterCap = _preFilterCap;
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uniquenessRatio = _uniquenessRatio;
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speckleWindowSize = _speckleWindowSize;
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speckleRange = _speckleRange;
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fullDP = _fullDP;
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sm = createStereoSGBM(0, 0, 0);
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}
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StereoSGBM::~StereoSGBM()
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{
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}
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void StereoSGBM::operator ()( InputArray _left, InputArray _right,
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OutputArray _disp )
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{
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sm->set("minDisparity", minDisparity);
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sm->set("numDisparities", numberOfDisparities);
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sm->set("SADWindowSize", SADWindowSize);
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sm->set("P1", P1);
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sm->set("P2", P2);
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sm->set("disp12MaxDiff", disp12MaxDiff);
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sm->set("preFilterCap", preFilterCap);
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sm->set("uniquenessRatio", uniquenessRatio);
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sm->set("speckleWindowSize", speckleWindowSize);
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sm->set("speckleRange", speckleRange);
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sm->set("fullDP", fullDP);
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sm->compute(_left, _right, _disp);
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}
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}
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@ -7,10 +7,11 @@
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// License Agreement
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// For Open Source Computer Vision Library
|
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
|
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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@ -23,7 +24,7 @@
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// * The name of the copyright holders may not be used to endorse or promote products
|
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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@ -46,58 +47,45 @@
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#include "precomp.hpp"
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#include <stdio.h>
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//#undef CV_SSE2
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//#define CV_SSE2 0
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//#include "emmintrin.h"
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#include <limits>
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CV_IMPL CvStereoBMState* cvCreateStereoBMState( int /*preset*/, int numberOfDisparities )
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{
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CvStereoBMState* state = (CvStereoBMState*)cvAlloc( sizeof(*state) );
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if( !state )
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return 0;
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state->preFilterType = CV_STEREO_BM_XSOBEL; //CV_STEREO_BM_NORMALIZED_RESPONSE;
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state->preFilterSize = 9;
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state->preFilterCap = 31;
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state->SADWindowSize = 15;
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state->minDisparity = 0;
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state->numberOfDisparities = numberOfDisparities > 0 ? numberOfDisparities : 64;
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state->textureThreshold = 10;
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state->uniquenessRatio = 15;
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state->speckleRange = state->speckleWindowSize = 0;
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state->trySmallerWindows = 0;
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state->roi1 = state->roi2 = cvRect(0,0,0,0);
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state->disp12MaxDiff = -1;
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state->preFilteredImg0 = state->preFilteredImg1 = state->slidingSumBuf =
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state->disp = state->cost = 0;
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return state;
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}
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CV_IMPL void cvReleaseStereoBMState( CvStereoBMState** state )
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{
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if( !state )
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CV_Error( CV_StsNullPtr, "" );
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if( !*state )
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return;
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cvReleaseMat( &(*state)->preFilteredImg0 );
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cvReleaseMat( &(*state)->preFilteredImg1 );
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cvReleaseMat( &(*state)->slidingSumBuf );
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cvReleaseMat( &(*state)->disp );
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cvReleaseMat( &(*state)->cost );
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cvFree( state );
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}
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namespace cv
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{
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struct StereoBMParams
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{
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StereoBMParams(int _numDisparities=64, int _SADWindowSize=21)
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{
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preFilterType = STEREO_PREFILTER_XSOBEL;
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preFilterSize = 9;
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preFilterCap = 31;
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SADWindowSize = _SADWindowSize;
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minDisparity = 0;
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numDisparities = _numDisparities > 0 ? _numDisparities : 64;
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textureThreshold = 10;
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uniquenessRatio = 15;
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speckleRange = speckleWindowSize = 0;
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roi1 = roi2 = Rect(0,0,0,0);
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disp12MaxDiff = -1;
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dispType = CV_16S;
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}
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int preFilterType;
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int preFilterSize;
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int preFilterCap;
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int SADWindowSize;
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int minDisparity;
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int numDisparities;
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int textureThreshold;
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int uniquenessRatio;
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int speckleRange;
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int speckleWindowSize;
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Rect roi1, roi2;
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int disp12MaxDiff;
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int dispType;
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};
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static void prefilterNorm( const Mat& src, Mat& dst, int winsize, int ftzero, uchar* buf )
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{
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int x, y, wsz2 = winsize/2;
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@ -191,11 +179,11 @@ prefilterXSobel( const Mat& src, Mat& dst, int ftzero )
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dptr0[0] = dptr0[size.width-1] = dptr1[0] = dptr1[size.width-1] = val0;
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x = 1;
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#if CV_SSE2
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#if CV_SSE2
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if( useSIMD )
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{
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__m128i z = _mm_setzero_si128(), ftz = _mm_set1_epi16((short)ftzero),
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ftz2 = _mm_set1_epi8(CV_CAST_8U(ftzero*2));
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ftz2 = _mm_set1_epi8(CV_CAST_8U(ftzero*2));
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for( ; x <= size.width-9; x += 8 )
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{
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__m128i c0 = _mm_unpacklo_epi8(_mm_loadl_epi64((__m128i*)(srow0 + x - 1)), z);
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@ -223,12 +211,12 @@ prefilterXSobel( const Mat& src, Mat& dst, int ftzero )
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_mm_storel_epi64((__m128i*)(dptr1 + x), _mm_unpackhi_epi64(v0, v0));
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}
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}
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#endif
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#endif
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for( ; x < size.width-1; x++ )
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{
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int d0 = srow0[x+1] - srow0[x-1], d1 = srow1[x+1] - srow1[x-1],
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d2 = srow2[x+1] - srow2[x-1], d3 = srow3[x+1] - srow3[x-1];
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d2 = srow2[x+1] - srow2[x-1], d3 = srow3[x+1] - srow3[x-1];
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int v0 = tab[d0 + d1*2 + d2 + OFS];
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int v1 = tab[d1 + d2*2 + d3 + OFS];
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dptr0[x] = (uchar)v0;
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@ -249,14 +237,14 @@ static const int DISPARITY_SHIFT = 4;
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#if CV_SSE2
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static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
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Mat& disp, Mat& cost, CvStereoBMState& state,
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||||
uchar* buf, int _dy0, int _dy1 )
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||||
Mat& disp, Mat& cost, StereoBMParams& state,
|
||||
uchar* buf, int _dy0, int _dy1 )
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{
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const int ALIGN = 16;
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int x, y, d;
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int wsz = state.SADWindowSize, wsz2 = wsz/2;
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int dy0 = MIN(_dy0, wsz2+1), dy1 = MIN(_dy1, wsz2+1);
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int ndisp = state.numberOfDisparities;
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int ndisp = state.numDisparities;
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int mindisp = state.minDisparity;
|
||||
int lofs = MAX(ndisp - 1 + mindisp, 0);
|
||||
int rofs = -MIN(ndisp - 1 + mindisp, 0);
|
||||
@ -343,7 +331,7 @@ static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
|
||||
rptr = rptr0 + MIN(MAX(x1, -rofs), width-1-rofs) - dy0*sstep;
|
||||
|
||||
for( y = -dy0; y < height + dy1; y++, cbuf += ndisp, cbuf_sub += ndisp,
|
||||
hsad += ndisp, lptr += sstep, lptr_sub += sstep, rptr += sstep )
|
||||
hsad += ndisp, lptr += sstep, lptr_sub += sstep, rptr += sstep )
|
||||
{
|
||||
int lval = lptr[0];
|
||||
__m128i lv = _mm_set1_epi8((char)lval), z = _mm_setzero_si128();
|
||||
@ -464,7 +452,7 @@ static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
|
||||
__m128i thresh8 = _mm_set1_epi16((short)(thresh + 1));
|
||||
__m128i d1 = _mm_set1_epi16((short)(mind-1)), d2 = _mm_set1_epi16((short)(mind+1));
|
||||
__m128i dd_16 = _mm_add_epi16(dd_8, dd_8);
|
||||
d8 = _mm_sub_epi16(d0_8, dd_16);
|
||||
d8 = _mm_sub_epi16(d0_8, dd_16);
|
||||
|
||||
for( d = 0; d < ndisp; d += 16 )
|
||||
{
|
||||
@ -507,14 +495,14 @@ static void findStereoCorrespondenceBM_SSE2( const Mat& left, const Mat& right,
|
||||
|
||||
static void
|
||||
findStereoCorrespondenceBM( const Mat& left, const Mat& right,
|
||||
Mat& disp, Mat& cost, const CvStereoBMState& state,
|
||||
uchar* buf, int _dy0, int _dy1 )
|
||||
Mat& disp, Mat& cost, const StereoBMParams& state,
|
||||
uchar* buf, int _dy0, int _dy1 )
|
||||
{
|
||||
const int ALIGN = 16;
|
||||
int x, y, d;
|
||||
int wsz = state.SADWindowSize, wsz2 = wsz/2;
|
||||
int dy0 = MIN(_dy0, wsz2+1), dy1 = MIN(_dy1, wsz2+1);
|
||||
int ndisp = state.numberOfDisparities;
|
||||
int ndisp = state.numDisparities;
|
||||
int mindisp = state.minDisparity;
|
||||
int lofs = MAX(ndisp - 1 + mindisp, 0);
|
||||
int rofs = -MIN(ndisp - 1 + mindisp, 0);
|
||||
@ -592,7 +580,7 @@ findStereoCorrespondenceBM( const Mat& left, const Mat& right,
|
||||
rptr = rptr0 + MIN(MAX(x1, -rofs), width-1-rofs) - dy0*sstep;
|
||||
|
||||
for( y = -dy0; y < height + dy1; y++, cbuf += ndisp, cbuf_sub += ndisp,
|
||||
hsad += ndisp, lptr += sstep, lptr_sub += sstep, rptr += sstep )
|
||||
hsad += ndisp, lptr += sstep, lptr_sub += sstep, rptr += sstep )
|
||||
{
|
||||
int lval = lptr[0];
|
||||
for( d = 0; d < ndisp; d++ )
|
||||
@ -662,21 +650,21 @@ findStereoCorrespondenceBM( const Mat& left, const Mat& right,
|
||||
}
|
||||
|
||||
{
|
||||
sad[-1] = sad[1];
|
||||
sad[ndisp] = sad[ndisp-2];
|
||||
int p = sad[mind+1], n = sad[mind-1];
|
||||
d = p + n - 2*sad[mind] + std::abs(p - n);
|
||||
dptr[y*dstep] = (short)(((ndisp - mind - 1 + mindisp)*256 + (d != 0 ? (p-n)*256/d : 0) + 15) >> 4);
|
||||
costptr[y*coststep] = sad[mind];
|
||||
sad[-1] = sad[1];
|
||||
sad[ndisp] = sad[ndisp-2];
|
||||
int p = sad[mind+1], n = sad[mind-1];
|
||||
d = p + n - 2*sad[mind] + std::abs(p - n);
|
||||
dptr[y*dstep] = (short)(((ndisp - mind - 1 + mindisp)*256 + (d != 0 ? (p-n)*256/d : 0) + 15) >> 4);
|
||||
costptr[y*coststep] = sad[mind];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
struct PrefilterInvoker
|
||||
struct PrefilterInvoker : public ParallelLoopBody
|
||||
{
|
||||
PrefilterInvoker(const Mat& left0, const Mat& right0, Mat& left, Mat& right,
|
||||
uchar* buf0, uchar* buf1, CvStereoBMState* _state )
|
||||
uchar* buf0, uchar* buf1, StereoBMParams* _state)
|
||||
{
|
||||
imgs0[0] = &left0; imgs0[1] = &right0;
|
||||
imgs[0] = &left; imgs[1] = &right;
|
||||
@ -684,41 +672,47 @@ struct PrefilterInvoker
|
||||
state = _state;
|
||||
}
|
||||
|
||||
void operator()( int ind ) const
|
||||
void operator()( const Range& range ) const
|
||||
{
|
||||
if( state->preFilterType == CV_STEREO_BM_NORMALIZED_RESPONSE )
|
||||
prefilterNorm( *imgs0[ind], *imgs[ind], state->preFilterSize, state->preFilterCap, buf[ind] );
|
||||
else
|
||||
prefilterXSobel( *imgs0[ind], *imgs[ind], state->preFilterCap );
|
||||
for( int i = range.start; i < range.end; i++ )
|
||||
{
|
||||
if( state->preFilterType == STEREO_PREFILTER_NORMALIZED_RESPONSE )
|
||||
prefilterNorm( *imgs0[i], *imgs[i], state->preFilterSize, state->preFilterCap, buf[i] );
|
||||
else
|
||||
prefilterXSobel( *imgs0[i], *imgs[i], state->preFilterCap );
|
||||
}
|
||||
}
|
||||
|
||||
const Mat* imgs0[2];
|
||||
Mat* imgs[2];
|
||||
uchar* buf[2];
|
||||
CvStereoBMState *state;
|
||||
StereoBMParams* state;
|
||||
};
|
||||
|
||||
|
||||
struct FindStereoCorrespInvoker
|
||||
struct FindStereoCorrespInvoker : public ParallelLoopBody
|
||||
{
|
||||
FindStereoCorrespInvoker( const Mat& _left, const Mat& _right,
|
||||
Mat& _disp, CvStereoBMState* _state,
|
||||
int _nstripes, int _stripeBufSize,
|
||||
bool _useShorts, Rect _validDisparityRect )
|
||||
Mat& _disp, StereoBMParams* _state,
|
||||
int _nstripes, size_t _stripeBufSize,
|
||||
bool _useShorts, Rect _validDisparityRect,
|
||||
Mat& _slidingSumBuf, Mat& _cost )
|
||||
{
|
||||
left = &_left; right = &_right;
|
||||
disp = &_disp; state = _state;
|
||||
nstripes = _nstripes; stripeBufSize = _stripeBufSize;
|
||||
useShorts = _useShorts;
|
||||
validDisparityRect = _validDisparityRect;
|
||||
slidingSumBuf = &_slidingSumBuf;
|
||||
cost = &_cost;
|
||||
}
|
||||
|
||||
void operator()( const BlockedRange& range ) const
|
||||
void operator()( const Range& range ) const
|
||||
{
|
||||
int cols = left->cols, rows = left->rows;
|
||||
int _row0 = std::min(cvRound(range.begin() * rows / nstripes), rows);
|
||||
int _row1 = std::min(cvRound(range.end() * rows / nstripes), rows);
|
||||
uchar *ptr = state->slidingSumBuf->data.ptr + range.begin() * stripeBufSize;
|
||||
int _row0 = std::min(cvRound(range.start * rows / nstripes), rows);
|
||||
int _row1 = std::min(cvRound(range.end * rows / nstripes), rows);
|
||||
uchar *ptr = slidingSumBuf->data + range.start * stripeBufSize;
|
||||
int FILTERED = (state->minDisparity - 1)*16;
|
||||
|
||||
Rect roi = validDisparityRect & Rect(0, _row0, cols, _row1 - _row0);
|
||||
@ -742,7 +736,7 @@ struct FindStereoCorrespInvoker
|
||||
Mat left_i = left->rowRange(row0, row1);
|
||||
Mat right_i = right->rowRange(row0, row1);
|
||||
Mat disp_i = disp->rowRange(row0, row1);
|
||||
Mat cost_i = state->disp12MaxDiff >= 0 ? Mat(state->cost).rowRange(row0, row1) : Mat();
|
||||
Mat cost_i = state->disp12MaxDiff >= 0 ? cost->rowRange(row0, row1) : Mat();
|
||||
|
||||
#if CV_SSE2
|
||||
if( useShorts )
|
||||
@ -752,7 +746,7 @@ struct FindStereoCorrespInvoker
|
||||
findStereoCorrespondenceBM( left_i, right_i, disp_i, cost_i, *state, ptr, row0, rows - row1 );
|
||||
|
||||
if( state->disp12MaxDiff >= 0 )
|
||||
validateDisparity( disp_i, cost_i, state->minDisparity, state->numberOfDisparities, state->disp12MaxDiff );
|
||||
validateDisparity( disp_i, cost_i, state->minDisparity, state->numDisparities, state->disp12MaxDiff );
|
||||
|
||||
if( roi.x > 0 )
|
||||
{
|
||||
@ -768,185 +762,174 @@ struct FindStereoCorrespInvoker
|
||||
|
||||
protected:
|
||||
const Mat *left, *right;
|
||||
Mat* disp;
|
||||
CvStereoBMState *state;
|
||||
Mat* disp, *slidingSumBuf, *cost;
|
||||
StereoBMParams *state;
|
||||
|
||||
int nstripes;
|
||||
int stripeBufSize;
|
||||
size_t stripeBufSize;
|
||||
bool useShorts;
|
||||
Rect validDisparityRect;
|
||||
};
|
||||
|
||||
static void findStereoCorrespondenceBM( const Mat& left0, const Mat& right0, Mat& disp0, CvStereoBMState* state)
|
||||
|
||||
class StereoBMImpl : public StereoMatcher
|
||||
{
|
||||
if (left0.size() != right0.size() || disp0.size() != left0.size())
|
||||
CV_Error( CV_StsUnmatchedSizes, "All the images must have the same size" );
|
||||
|
||||
if (left0.type() != CV_8UC1 || right0.type() != CV_8UC1)
|
||||
CV_Error( CV_StsUnsupportedFormat, "Both input images must have CV_8UC1" );
|
||||
|
||||
if (disp0.type() != CV_16SC1 && disp0.type() != CV_32FC1)
|
||||
CV_Error( CV_StsUnsupportedFormat, "Disparity image must have CV_16SC1 or CV_32FC1 format" );
|
||||
|
||||
if( !state )
|
||||
CV_Error( CV_StsNullPtr, "Stereo BM state is NULL." );
|
||||
|
||||
if( state->preFilterType != CV_STEREO_BM_NORMALIZED_RESPONSE && state->preFilterType != CV_STEREO_BM_XSOBEL )
|
||||
CV_Error( CV_StsOutOfRange, "preFilterType must be = CV_STEREO_BM_NORMALIZED_RESPONSE" );
|
||||
|
||||
if( state->preFilterSize < 5 || state->preFilterSize > 255 || state->preFilterSize % 2 == 0 )
|
||||
CV_Error( CV_StsOutOfRange, "preFilterSize must be odd and be within 5..255" );
|
||||
|
||||
if( state->preFilterCap < 1 || state->preFilterCap > 63 )
|
||||
CV_Error( CV_StsOutOfRange, "preFilterCap must be within 1..63" );
|
||||
|
||||
if( state->SADWindowSize < 5 || state->SADWindowSize > 255 || state->SADWindowSize % 2 == 0 ||
|
||||
state->SADWindowSize >= std::min(left0.cols, left0.rows) )
|
||||
CV_Error( CV_StsOutOfRange, "SADWindowSize must be odd, be within 5..255 and be not larger than image width or height" );
|
||||
|
||||
if( state->numberOfDisparities <= 0 || state->numberOfDisparities % 16 != 0 )
|
||||
CV_Error( CV_StsOutOfRange, "numberOfDisparities must be positive and divisble by 16" );
|
||||
|
||||
if( state->textureThreshold < 0 )
|
||||
CV_Error( CV_StsOutOfRange, "texture threshold must be non-negative" );
|
||||
|
||||
if( state->uniquenessRatio < 0 )
|
||||
CV_Error( CV_StsOutOfRange, "uniqueness ratio must be non-negative" );
|
||||
|
||||
if( !state->preFilteredImg0 || state->preFilteredImg0->cols * state->preFilteredImg0->rows < left0.cols * left0.rows )
|
||||
public:
|
||||
StereoBMImpl()
|
||||
{
|
||||
cvReleaseMat( &state->preFilteredImg0 );
|
||||
cvReleaseMat( &state->preFilteredImg1 );
|
||||
cvReleaseMat( &state->cost );
|
||||
|
||||
state->preFilteredImg0 = cvCreateMat( left0.rows, left0.cols, CV_8U );
|
||||
state->preFilteredImg1 = cvCreateMat( left0.rows, left0.cols, CV_8U );
|
||||
state->cost = cvCreateMat( left0.rows, left0.cols, CV_16S );
|
||||
}
|
||||
Mat left(left0.size(), CV_8U, state->preFilteredImg0->data.ptr);
|
||||
Mat right(right0.size(), CV_8U, state->preFilteredImg1->data.ptr);
|
||||
|
||||
int mindisp = state->minDisparity;
|
||||
int ndisp = state->numberOfDisparities;
|
||||
|
||||
int width = left0.cols;
|
||||
int height = left0.rows;
|
||||
int lofs = std::max(ndisp - 1 + mindisp, 0);
|
||||
int rofs = -std::min(ndisp - 1 + mindisp, 0);
|
||||
int width1 = width - rofs - ndisp + 1;
|
||||
int FILTERED = (state->minDisparity - 1) << DISPARITY_SHIFT;
|
||||
|
||||
if( lofs >= width || rofs >= width || width1 < 1 )
|
||||
{
|
||||
disp0 = Scalar::all( FILTERED * ( disp0.type() < CV_32F ? 1 : 1./(1 << DISPARITY_SHIFT) ) );
|
||||
return;
|
||||
params = StereoBMParams();
|
||||
}
|
||||
|
||||
Mat disp = disp0;
|
||||
|
||||
if( disp0.type() == CV_32F)
|
||||
StereoBMImpl( int _numDisparities, int _SADWindowSize )
|
||||
{
|
||||
if( !state->disp || state->disp->rows != disp0.rows || state->disp->cols != disp0.cols )
|
||||
params = StereoBMParams(_numDisparities, _SADWindowSize);
|
||||
}
|
||||
|
||||
void compute( InputArray leftarr, InputArray rightarr, OutputArray disparr )
|
||||
{
|
||||
Mat left0 = leftarr.getMat(), right0 = rightarr.getMat();
|
||||
int dtype = disparr.fixedType() ? disparr.type() : params.dispType;
|
||||
|
||||
if (left0.size() != right0.size())
|
||||
CV_Error( CV_StsUnmatchedSizes, "All the images must have the same size" );
|
||||
|
||||
if (left0.type() != CV_8UC1 || right0.type() != CV_8UC1)
|
||||
CV_Error( CV_StsUnsupportedFormat, "Both input images must have CV_8UC1" );
|
||||
|
||||
if (dtype != CV_16SC1 && dtype != CV_32FC1)
|
||||
CV_Error( CV_StsUnsupportedFormat, "Disparity image must have CV_16SC1 or CV_32FC1 format" );
|
||||
|
||||
disparr.create(left0.size(), dtype);
|
||||
Mat disp0 = disparr.getMat();
|
||||
|
||||
if( params.preFilterType != STEREO_PREFILTER_NORMALIZED_RESPONSE &&
|
||||
params.preFilterType != STEREO_PREFILTER_XSOBEL )
|
||||
CV_Error( CV_StsOutOfRange, "preFilterType must be = CV_STEREO_BM_NORMALIZED_RESPONSE" );
|
||||
|
||||
if( params.preFilterSize < 5 || params.preFilterSize > 255 || params.preFilterSize % 2 == 0 )
|
||||
CV_Error( CV_StsOutOfRange, "preFilterSize must be odd and be within 5..255" );
|
||||
|
||||
if( params.preFilterCap < 1 || params.preFilterCap > 63 )
|
||||
CV_Error( CV_StsOutOfRange, "preFilterCap must be within 1..63" );
|
||||
|
||||
if( params.SADWindowSize < 5 || params.SADWindowSize > 255 || params.SADWindowSize % 2 == 0 ||
|
||||
params.SADWindowSize >= std::min(left0.cols, left0.rows) )
|
||||
CV_Error( CV_StsOutOfRange, "SADWindowSize must be odd, be within 5..255 and be not larger than image width or height" );
|
||||
|
||||
if( params.numDisparities <= 0 || params.numDisparities % 16 != 0 )
|
||||
CV_Error( CV_StsOutOfRange, "numDisparities must be positive and divisble by 16" );
|
||||
|
||||
if( params.textureThreshold < 0 )
|
||||
CV_Error( CV_StsOutOfRange, "texture threshold must be non-negative" );
|
||||
|
||||
if( params.uniquenessRatio < 0 )
|
||||
CV_Error( CV_StsOutOfRange, "uniqueness ratio must be non-negative" );
|
||||
|
||||
preFilteredImg0.create( left0.size(), CV_8U );
|
||||
preFilteredImg1.create( left0.size(), CV_8U );
|
||||
cost.create( left0.size(), CV_16S );
|
||||
|
||||
Mat left = preFilteredImg0, right = preFilteredImg1;
|
||||
|
||||
int mindisp = params.minDisparity;
|
||||
int ndisp = params.numDisparities;
|
||||
|
||||
int width = left0.cols;
|
||||
int height = left0.rows;
|
||||
int lofs = std::max(ndisp - 1 + mindisp, 0);
|
||||
int rofs = -std::min(ndisp - 1 + mindisp, 0);
|
||||
int width1 = width - rofs - ndisp + 1;
|
||||
int FILTERED = (params.minDisparity - 1) << DISPARITY_SHIFT;
|
||||
|
||||
if( lofs >= width || rofs >= width || width1 < 1 )
|
||||
{
|
||||
cvReleaseMat( &state->disp );
|
||||
state->disp = cvCreateMat(disp0.rows, disp0.cols, CV_16S);
|
||||
disp0 = Scalar::all( FILTERED * ( disp0.type() < CV_32F ? 1 : 1./(1 << DISPARITY_SHIFT) ) );
|
||||
return;
|
||||
}
|
||||
disp = cv::cvarrToMat(state->disp);
|
||||
}
|
||||
|
||||
int wsz = state->SADWindowSize;
|
||||
int bufSize0 = (int)((ndisp + 2)*sizeof(int));
|
||||
bufSize0 += (int)((height+wsz+2)*ndisp*sizeof(int));
|
||||
bufSize0 += (int)((height + wsz + 2)*sizeof(int));
|
||||
bufSize0 += (int)((height+wsz+2)*ndisp*(wsz+2)*sizeof(uchar) + 256);
|
||||
Mat disp = disp0;
|
||||
if( dtype == CV_32F )
|
||||
{
|
||||
dispbuf.create(disp0.size(), CV_16S);
|
||||
disp = dispbuf;
|
||||
}
|
||||
|
||||
int bufSize1 = (int)((width + state->preFilterSize + 2) * sizeof(int) + 256);
|
||||
int bufSize2 = 0;
|
||||
if( state->speckleRange >= 0 && state->speckleWindowSize > 0 )
|
||||
bufSize2 = width*height*(sizeof(cv::Point_<short>) + sizeof(int) + sizeof(uchar));
|
||||
int wsz = params.SADWindowSize;
|
||||
int bufSize0 = (int)((ndisp + 2)*sizeof(int));
|
||||
bufSize0 += (int)((height+wsz+2)*ndisp*sizeof(int));
|
||||
bufSize0 += (int)((height + wsz + 2)*sizeof(int));
|
||||
bufSize0 += (int)((height+wsz+2)*ndisp*(wsz+2)*sizeof(uchar) + 256);
|
||||
|
||||
int bufSize1 = (int)((width + params.preFilterSize + 2) * sizeof(int) + 256);
|
||||
int bufSize2 = 0;
|
||||
if( params.speckleRange >= 0 && params.speckleWindowSize > 0 )
|
||||
bufSize2 = width*height*(sizeof(Point_<short>) + sizeof(int) + sizeof(uchar));
|
||||
|
||||
#if CV_SSE2
|
||||
bool useShorts = state->preFilterCap <= 31 && state->SADWindowSize <= 21 && checkHardwareSupport(CV_CPU_SSE2);
|
||||
bool useShorts = params.preFilterCap <= 31 && params.SADWindowSize <= 21 && checkHardwareSupport(CV_CPU_SSE2);
|
||||
#else
|
||||
const bool useShorts = false;
|
||||
const bool useShorts = false;
|
||||
#endif
|
||||
|
||||
#ifdef HAVE_TBB
|
||||
const double SAD_overhead_coeff = 10.0;
|
||||
double N0 = 8000000 / (useShorts ? 1 : 4); // approx tbb's min number instructions reasonable for one thread
|
||||
double maxStripeSize = std::min(std::max(N0 / (width * ndisp), (wsz-1) * SAD_overhead_coeff), (double)height);
|
||||
int nstripes = cvCeil(height / maxStripeSize);
|
||||
#else
|
||||
const int nstripes = 1;
|
||||
#endif
|
||||
const double SAD_overhead_coeff = 10.0;
|
||||
double N0 = 8000000 / (useShorts ? 1 : 4); // approx tbb's min number instructions reasonable for one thread
|
||||
double maxStripeSize = std::min(std::max(N0 / (width * ndisp), (wsz-1) * SAD_overhead_coeff), (double)height);
|
||||
int nstripes = cvCeil(height / maxStripeSize);
|
||||
int bufSize = std::max(bufSize0 * nstripes, std::max(bufSize1 * 2, bufSize2));
|
||||
|
||||
int bufSize = std::max(bufSize0 * nstripes, std::max(bufSize1 * 2, bufSize2));
|
||||
if( slidingSumBuf.cols < bufSize )
|
||||
slidingSumBuf.create( 1, bufSize, CV_8U );
|
||||
|
||||
if( !state->slidingSumBuf || state->slidingSumBuf->cols < bufSize )
|
||||
{
|
||||
cvReleaseMat( &state->slidingSumBuf );
|
||||
state->slidingSumBuf = cvCreateMat( 1, bufSize, CV_8U );
|
||||
uchar *_buf = slidingSumBuf.data;
|
||||
parallel_for_(Range(0, 2), PrefilterInvoker(left0, right0, left, right, _buf, _buf + bufSize1, ¶ms), 1);
|
||||
|
||||
Rect validDisparityRect(0, 0, width, height), R1 = params.roi1, R2 = params.roi2;
|
||||
validDisparityRect = getValidDisparityROI(R1.area() > 0 ? Rect(0, 0, width, height) : validDisparityRect,
|
||||
R2.area() > 0 ? Rect(0, 0, width, height) : validDisparityRect,
|
||||
params.minDisparity, params.numDisparities,
|
||||
params.SADWindowSize);
|
||||
|
||||
parallel_for_(Range(0, nstripes),
|
||||
FindStereoCorrespInvoker(left, right, disp, ¶ms, nstripes,
|
||||
bufSize0, useShorts, validDisparityRect,
|
||||
slidingSumBuf, cost));
|
||||
|
||||
if( params.speckleRange >= 0 && params.speckleWindowSize > 0 )
|
||||
filterSpeckles(disp, FILTERED, params.speckleWindowSize, params.speckleRange, slidingSumBuf);
|
||||
|
||||
if (disp0.data != disp.data)
|
||||
disp.convertTo(disp0, disp0.type(), 1./(1 << DISPARITY_SHIFT), 0);
|
||||
}
|
||||
|
||||
uchar *_buf = state->slidingSumBuf->data.ptr;
|
||||
int idx[] = {0,1};
|
||||
parallel_do(idx, idx+2, PrefilterInvoker(left0, right0, left, right, _buf, _buf + bufSize1, state));
|
||||
AlgorithmInfo* info() const;
|
||||
|
||||
Rect validDisparityRect(0, 0, width, height), R1 = state->roi1, R2 = state->roi2;
|
||||
validDisparityRect = getValidDisparityROI(R1.area() > 0 ? Rect(0, 0, width, height) : validDisparityRect,
|
||||
R2.area() > 0 ? Rect(0, 0, width, height) : validDisparityRect,
|
||||
state->minDisparity, state->numberOfDisparities,
|
||||
state->SADWindowSize);
|
||||
StereoBMParams params;
|
||||
Mat preFilteredImg0, preFilteredImg1, cost, dispbuf;
|
||||
Mat slidingSumBuf;
|
||||
};
|
||||
|
||||
parallel_for(BlockedRange(0, nstripes),
|
||||
FindStereoCorrespInvoker(left, right, disp, state, nstripes,
|
||||
bufSize0, useShorts, validDisparityRect));
|
||||
#define add_param(n) \
|
||||
obj.info()->addParam(obj, #n, obj.params.n)
|
||||
|
||||
if( state->speckleRange >= 0 && state->speckleWindowSize > 0 )
|
||||
{
|
||||
Mat buf(state->slidingSumBuf);
|
||||
filterSpeckles(disp, FILTERED, state->speckleWindowSize, state->speckleRange, buf);
|
||||
}
|
||||
CV_INIT_ALGORITHM(StereoBMImpl, "StereoMatcher.BM",
|
||||
add_param(preFilterType);
|
||||
add_param(preFilterSize);
|
||||
add_param(preFilterCap);
|
||||
add_param(SADWindowSize);
|
||||
add_param(minDisparity);
|
||||
add_param(numDisparities);
|
||||
add_param(textureThreshold);
|
||||
add_param(uniquenessRatio);
|
||||
add_param(speckleRange);
|
||||
add_param(speckleWindowSize);
|
||||
add_param(disp12MaxDiff);
|
||||
add_param(dispType));
|
||||
|
||||
if (disp0.data != disp.data)
|
||||
disp.convertTo(disp0, disp0.type(), 1./(1 << DISPARITY_SHIFT), 0);
|
||||
}
|
||||
|
||||
StereoBM::StereoBM()
|
||||
{ state = cvCreateStereoBMState(); }
|
||||
|
||||
StereoBM::StereoBM(int _preset, int _ndisparities, int _SADWindowSize)
|
||||
{ init(_preset, _ndisparities, _SADWindowSize); }
|
||||
|
||||
void StereoBM::init(int _preset, int _ndisparities, int _SADWindowSize)
|
||||
cv::Ptr<cv::StereoMatcher> cv::createStereoBM(int _numDisparities, int _SADWindowSize)
|
||||
{
|
||||
state = cvCreateStereoBMState(_preset, _ndisparities);
|
||||
state->SADWindowSize = _SADWindowSize;
|
||||
}
|
||||
|
||||
void StereoBM::operator()( InputArray _left, InputArray _right,
|
||||
OutputArray _disparity, int disptype )
|
||||
{
|
||||
Mat left = _left.getMat(), right = _right.getMat();
|
||||
CV_Assert( disptype == CV_16S || disptype == CV_32F );
|
||||
_disparity.create(left.size(), disptype);
|
||||
Mat disparity = _disparity.getMat();
|
||||
|
||||
findStereoCorrespondenceBM(left, right, disparity, state);
|
||||
}
|
||||
|
||||
template<> void Ptr<CvStereoBMState>::delete_obj()
|
||||
{ cvReleaseStereoBMState(&obj); }
|
||||
|
||||
}
|
||||
|
||||
CV_IMPL void cvFindStereoCorrespondenceBM( const CvArr* leftarr, const CvArr* rightarr,
|
||||
CvArr* disparr, CvStereoBMState* state )
|
||||
{
|
||||
cv::Mat left = cv::cvarrToMat(leftarr),
|
||||
right = cv::cvarrToMat(rightarr),
|
||||
disp = cv::cvarrToMat(disparr);
|
||||
cv::findStereoCorrespondenceBM(left, right, disp, state);
|
||||
return new StereoBMImpl(_numDisparities, _SADWindowSize);
|
||||
}
|
||||
|
||||
/* End of file. */
|
||||
|
@ -12,6 +12,7 @@
|
||||
//
|
||||
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
||||
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
|
||||
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
|
||||
// Third party copyrights are property of their respective owners.
|
||||
//
|
||||
// Redistribution and use in source and binary forms, with or without modification,
|
||||
@ -61,42 +62,52 @@ typedef short DispType;
|
||||
|
||||
enum { NR = 16, NR2 = NR/2 };
|
||||
|
||||
StereoSGBM::StereoSGBM()
|
||||
|
||||
struct StereoSGBMParams
|
||||
{
|
||||
minDisparity = numberOfDisparities = 0;
|
||||
SADWindowSize = 0;
|
||||
P1 = P2 = 0;
|
||||
disp12MaxDiff = 0;
|
||||
preFilterCap = 0;
|
||||
uniquenessRatio = 0;
|
||||
speckleWindowSize = 0;
|
||||
speckleRange = 0;
|
||||
fullDP = false;
|
||||
}
|
||||
StereoSGBMParams()
|
||||
{
|
||||
minDisparity = numDisparities = 0;
|
||||
SADWindowSize = 0;
|
||||
P1 = P2 = 0;
|
||||
disp12MaxDiff = 0;
|
||||
preFilterCap = 0;
|
||||
uniquenessRatio = 0;
|
||||
speckleWindowSize = 0;
|
||||
speckleRange = 0;
|
||||
fullDP = false;
|
||||
}
|
||||
|
||||
StereoSGBMParams( int _minDisparity, int _numDisparities, int _SADWindowSize,
|
||||
int _P1, int _P2, int _disp12MaxDiff, int _preFilterCap,
|
||||
int _uniquenessRatio, int _speckleWindowSize, int _speckleRange,
|
||||
bool _fullDP )
|
||||
{
|
||||
minDisparity = _minDisparity;
|
||||
numDisparities = _numDisparities;
|
||||
SADWindowSize = _SADWindowSize;
|
||||
P1 = _P1;
|
||||
P2 = _P2;
|
||||
disp12MaxDiff = _disp12MaxDiff;
|
||||
preFilterCap = _preFilterCap;
|
||||
uniquenessRatio = _uniquenessRatio;
|
||||
speckleWindowSize = _speckleWindowSize;
|
||||
speckleRange = _speckleRange;
|
||||
fullDP = _fullDP;
|
||||
}
|
||||
|
||||
StereoSGBM::StereoSGBM( int _minDisparity, int _numDisparities, int _SADWindowSize,
|
||||
int _P1, int _P2, int _disp12MaxDiff, int _preFilterCap,
|
||||
int _uniquenessRatio, int _speckleWindowSize, int _speckleRange,
|
||||
bool _fullDP )
|
||||
{
|
||||
minDisparity = _minDisparity;
|
||||
numberOfDisparities = _numDisparities;
|
||||
SADWindowSize = _SADWindowSize;
|
||||
P1 = _P1;
|
||||
P2 = _P2;
|
||||
disp12MaxDiff = _disp12MaxDiff;
|
||||
preFilterCap = _preFilterCap;
|
||||
uniquenessRatio = _uniquenessRatio;
|
||||
speckleWindowSize = _speckleWindowSize;
|
||||
speckleRange = _speckleRange;
|
||||
fullDP = _fullDP;
|
||||
}
|
||||
|
||||
|
||||
StereoSGBM::~StereoSGBM()
|
||||
{
|
||||
}
|
||||
int minDisparity;
|
||||
int numDisparities;
|
||||
int SADWindowSize;
|
||||
int preFilterCap;
|
||||
int uniquenessRatio;
|
||||
int P1;
|
||||
int P2;
|
||||
int speckleWindowSize;
|
||||
int speckleRange;
|
||||
int disp12MaxDiff;
|
||||
bool fullDP;
|
||||
};
|
||||
|
||||
/*
|
||||
For each pixel row1[x], max(-maxD, 0) <= minX <= x < maxX <= width - max(0, -minD),
|
||||
@ -289,7 +300,7 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
|
||||
final after all the tiles are processed.
|
||||
|
||||
the disparity in disp1buf is written with sub-pixel accuracy
|
||||
(4 fractional bits, see CvStereoSGBM::DISP_SCALE),
|
||||
(4 fractional bits, see StereoSGBM::DISP_SCALE),
|
||||
using quadratic interpolation, while the disparity in disp2buf
|
||||
is written as is, without interpolation.
|
||||
|
||||
@ -297,7 +308,7 @@ static void calcPixelCostBT( const Mat& img1, const Mat& img2, int y,
|
||||
It contains the minimum current cost, used to find the best disparity, corresponding to the minimal cost.
|
||||
*/
|
||||
static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
|
||||
Mat& disp1, const StereoSGBM& params,
|
||||
Mat& disp1, const StereoSGBMParams& params,
|
||||
Mat& buffer )
|
||||
{
|
||||
#if CV_SSE2
|
||||
@ -321,7 +332,7 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
|
||||
const int DISP_SCALE = StereoSGBM::DISP_SCALE;
|
||||
const CostType MAX_COST = SHRT_MAX;
|
||||
|
||||
int minD = params.minDisparity, maxD = minD + params.numberOfDisparities;
|
||||
int minD = params.minDisparity, maxD = minD + params.numDisparities;
|
||||
Size SADWindowSize;
|
||||
SADWindowSize.width = SADWindowSize.height = params.SADWindowSize > 0 ? params.SADWindowSize : 5;
|
||||
int ftzero = std::max(params.preFilterCap, 15) | 1;
|
||||
@ -817,26 +828,80 @@ static void computeDisparitySGBM( const Mat& img1, const Mat& img2,
|
||||
}
|
||||
}
|
||||
|
||||
typedef cv::Point_<short> Point2s;
|
||||
|
||||
void StereoSGBM::operator ()( InputArray _left, InputArray _right,
|
||||
OutputArray _disp )
|
||||
class StereoSGBMImpl : public StereoMatcher
|
||||
{
|
||||
Mat left = _left.getMat(), right = _right.getMat();
|
||||
CV_Assert( left.size() == right.size() && left.type() == right.type() &&
|
||||
left.depth() == DataType<PixType>::depth );
|
||||
public:
|
||||
StereoSGBMImpl()
|
||||
{
|
||||
params = StereoSGBMParams();
|
||||
}
|
||||
|
||||
_disp.create( left.size(), CV_16S );
|
||||
Mat disp = _disp.getMat();
|
||||
StereoSGBMImpl( int _minDisparity, int _numDisparities, int _SADWindowSize,
|
||||
int _P1, int _P2, int _disp12MaxDiff, int _preFilterCap,
|
||||
int _uniquenessRatio, int _speckleWindowSize, int _speckleRange,
|
||||
bool _fullDP )
|
||||
{
|
||||
params = StereoSGBMParams( _minDisparity, _numDisparities, _SADWindowSize,
|
||||
_P1, _P2, _disp12MaxDiff, _preFilterCap,
|
||||
_uniquenessRatio, _speckleWindowSize, _speckleRange,
|
||||
_fullDP );
|
||||
}
|
||||
|
||||
computeDisparitySGBM( left, right, disp, *this, buffer );
|
||||
medianBlur(disp, disp, 3);
|
||||
void compute( InputArray leftarr, InputArray rightarr, OutputArray disparr )
|
||||
{
|
||||
Mat left = leftarr.getMat(), right = rightarr.getMat();
|
||||
CV_Assert( left.size() == right.size() && left.type() == right.type() &&
|
||||
left.depth() == CV_8U );
|
||||
|
||||
if( speckleWindowSize > 0 )
|
||||
filterSpeckles(disp, (minDisparity - 1)*DISP_SCALE, speckleWindowSize, DISP_SCALE*speckleRange, buffer);
|
||||
disparr.create( left.size(), CV_16S );
|
||||
Mat disp = disparr.getMat();
|
||||
|
||||
computeDisparitySGBM( left, right, disp, params, buffer );
|
||||
medianBlur(disp, disp, 3);
|
||||
|
||||
if( params.speckleWindowSize > 0 )
|
||||
filterSpeckles(disp, (params.minDisparity - 1)*STEREO_DISP_SCALE, params.speckleWindowSize,
|
||||
STEREO_DISP_SCALE*params.speckleRange, buffer);
|
||||
}
|
||||
|
||||
AlgorithmInfo* info() const;
|
||||
|
||||
StereoSGBMParams params;
|
||||
Mat buffer;
|
||||
};
|
||||
|
||||
|
||||
Ptr<StereoMatcher> createStereoSGBM(int minDisparity, int numDisparities, int SADWindowSize,
|
||||
int P1, int P2, int disp12MaxDiff,
|
||||
int preFilterCap, int uniquenessRatio,
|
||||
int speckleWindowSize, int speckleRange,
|
||||
bool fullDP)
|
||||
{
|
||||
return new StereoSGBMImpl(minDisparity, numDisparities, SADWindowSize,
|
||||
P1, P2, disp12MaxDiff,
|
||||
preFilterCap, uniquenessRatio,
|
||||
speckleWindowSize, speckleRange,
|
||||
fullDP);
|
||||
}
|
||||
|
||||
|
||||
#define add_param(n) \
|
||||
obj.info()->addParam(obj, #n, obj.params.n)
|
||||
|
||||
CV_INIT_ALGORITHM(StereoSGBMImpl, "StereoMatcher.SGBM",
|
||||
add_param(minDisparity);
|
||||
add_param(numDisparities);
|
||||
add_param(SADWindowSize);
|
||||
add_param(preFilterCap);
|
||||
add_param(uniquenessRatio);
|
||||
add_param(P1);
|
||||
add_param(P2);
|
||||
add_param(speckleWindowSize);
|
||||
add_param(speckleRange);
|
||||
add_param(disp12MaxDiff);
|
||||
add_param(fullDP));
|
||||
|
||||
Rect getValidDisparityROI( Rect roi1, Rect roi2,
|
||||
int minDisparity,
|
||||
int numberOfDisparities,
|
||||
@ -855,108 +920,107 @@ Rect getValidDisparityROI( Rect roi1, Rect roi2,
|
||||
return r.width > 0 && r.height > 0 ? r : Rect();
|
||||
}
|
||||
|
||||
}
|
||||
typedef cv::Point_<short> Point2s;
|
||||
|
||||
namespace
|
||||
template <typename T>
|
||||
void filterSpecklesImpl(cv::Mat& img, int newVal, int maxSpeckleSize, int maxDiff, cv::Mat& _buf)
|
||||
{
|
||||
template <typename T>
|
||||
void filterSpecklesImpl(cv::Mat& img, int newVal, int maxSpeckleSize, int maxDiff, cv::Mat& _buf)
|
||||
using namespace cv;
|
||||
|
||||
int width = img.cols, height = img.rows, npixels = width*height;
|
||||
size_t bufSize = npixels*(int)(sizeof(Point2s) + sizeof(int) + sizeof(uchar));
|
||||
if( !_buf.isContinuous() || !_buf.data || _buf.cols*_buf.rows*_buf.elemSize() < bufSize )
|
||||
_buf.create(1, (int)bufSize, CV_8U);
|
||||
|
||||
uchar* buf = _buf.data;
|
||||
int i, j, dstep = (int)(img.step/sizeof(T));
|
||||
int* labels = (int*)buf;
|
||||
buf += npixels*sizeof(labels[0]);
|
||||
Point2s* wbuf = (Point2s*)buf;
|
||||
buf += npixels*sizeof(wbuf[0]);
|
||||
uchar* rtype = (uchar*)buf;
|
||||
int curlabel = 0;
|
||||
|
||||
// clear out label assignments
|
||||
memset(labels, 0, npixels*sizeof(labels[0]));
|
||||
|
||||
for( i = 0; i < height; i++ )
|
||||
{
|
||||
using namespace cv;
|
||||
T* ds = img.ptr<T>(i);
|
||||
int* ls = labels + width*i;
|
||||
|
||||
int width = img.cols, height = img.rows, npixels = width*height;
|
||||
size_t bufSize = npixels*(int)(sizeof(Point2s) + sizeof(int) + sizeof(uchar));
|
||||
if( !_buf.isContinuous() || !_buf.data || _buf.cols*_buf.rows*_buf.elemSize() < bufSize )
|
||||
_buf.create(1, (int)bufSize, CV_8U);
|
||||
|
||||
uchar* buf = _buf.data;
|
||||
int i, j, dstep = (int)(img.step/sizeof(T));
|
||||
int* labels = (int*)buf;
|
||||
buf += npixels*sizeof(labels[0]);
|
||||
Point2s* wbuf = (Point2s*)buf;
|
||||
buf += npixels*sizeof(wbuf[0]);
|
||||
uchar* rtype = (uchar*)buf;
|
||||
int curlabel = 0;
|
||||
|
||||
// clear out label assignments
|
||||
memset(labels, 0, npixels*sizeof(labels[0]));
|
||||
|
||||
for( i = 0; i < height; i++ )
|
||||
for( j = 0; j < width; j++ )
|
||||
{
|
||||
T* ds = img.ptr<T>(i);
|
||||
int* ls = labels + width*i;
|
||||
|
||||
for( j = 0; j < width; j++ )
|
||||
if( ds[j] != newVal ) // not a bad disparity
|
||||
{
|
||||
if( ds[j] != newVal ) // not a bad disparity
|
||||
if( ls[j] ) // has a label, check for bad label
|
||||
{
|
||||
if( ls[j] ) // has a label, check for bad label
|
||||
if( rtype[ls[j]] ) // small region, zero out disparity
|
||||
ds[j] = (T)newVal;
|
||||
}
|
||||
// no label, assign and propagate
|
||||
else
|
||||
{
|
||||
Point2s* ws = wbuf; // initialize wavefront
|
||||
Point2s p((short)j, (short)i); // current pixel
|
||||
curlabel++; // next label
|
||||
int count = 0; // current region size
|
||||
ls[j] = curlabel;
|
||||
|
||||
// wavefront propagation
|
||||
while( ws >= wbuf ) // wavefront not empty
|
||||
{
|
||||
if( rtype[ls[j]] ) // small region, zero out disparity
|
||||
ds[j] = (T)newVal;
|
||||
count++;
|
||||
// put neighbors onto wavefront
|
||||
T* dpp = &img.at<T>(p.y, p.x);
|
||||
T dp = *dpp;
|
||||
int* lpp = labels + width*p.y + p.x;
|
||||
|
||||
if( p.x < width-1 && !lpp[+1] && dpp[+1] != newVal && std::abs(dp - dpp[+1]) <= maxDiff )
|
||||
{
|
||||
lpp[+1] = curlabel;
|
||||
*ws++ = Point2s(p.x+1, p.y);
|
||||
}
|
||||
|
||||
if( p.x > 0 && !lpp[-1] && dpp[-1] != newVal && std::abs(dp - dpp[-1]) <= maxDiff )
|
||||
{
|
||||
lpp[-1] = curlabel;
|
||||
*ws++ = Point2s(p.x-1, p.y);
|
||||
}
|
||||
|
||||
if( p.y < height-1 && !lpp[+width] && dpp[+dstep] != newVal && std::abs(dp - dpp[+dstep]) <= maxDiff )
|
||||
{
|
||||
lpp[+width] = curlabel;
|
||||
*ws++ = Point2s(p.x, p.y+1);
|
||||
}
|
||||
|
||||
if( p.y > 0 && !lpp[-width] && dpp[-dstep] != newVal && std::abs(dp - dpp[-dstep]) <= maxDiff )
|
||||
{
|
||||
lpp[-width] = curlabel;
|
||||
*ws++ = Point2s(p.x, p.y-1);
|
||||
}
|
||||
|
||||
// pop most recent and propagate
|
||||
// NB: could try least recent, maybe better convergence
|
||||
p = *--ws;
|
||||
}
|
||||
|
||||
// assign label type
|
||||
if( count <= maxSpeckleSize ) // speckle region
|
||||
{
|
||||
rtype[ls[j]] = 1; // small region label
|
||||
ds[j] = (T)newVal;
|
||||
}
|
||||
// no label, assign and propagate
|
||||
else
|
||||
{
|
||||
Point2s* ws = wbuf; // initialize wavefront
|
||||
Point2s p((short)j, (short)i); // current pixel
|
||||
curlabel++; // next label
|
||||
int count = 0; // current region size
|
||||
ls[j] = curlabel;
|
||||
|
||||
// wavefront propagation
|
||||
while( ws >= wbuf ) // wavefront not empty
|
||||
{
|
||||
count++;
|
||||
// put neighbors onto wavefront
|
||||
T* dpp = &img.at<T>(p.y, p.x);
|
||||
T dp = *dpp;
|
||||
int* lpp = labels + width*p.y + p.x;
|
||||
|
||||
if( p.x < width-1 && !lpp[+1] && dpp[+1] != newVal && std::abs(dp - dpp[+1]) <= maxDiff )
|
||||
{
|
||||
lpp[+1] = curlabel;
|
||||
*ws++ = Point2s(p.x+1, p.y);
|
||||
}
|
||||
|
||||
if( p.x > 0 && !lpp[-1] && dpp[-1] != newVal && std::abs(dp - dpp[-1]) <= maxDiff )
|
||||
{
|
||||
lpp[-1] = curlabel;
|
||||
*ws++ = Point2s(p.x-1, p.y);
|
||||
}
|
||||
|
||||
if( p.y < height-1 && !lpp[+width] && dpp[+dstep] != newVal && std::abs(dp - dpp[+dstep]) <= maxDiff )
|
||||
{
|
||||
lpp[+width] = curlabel;
|
||||
*ws++ = Point2s(p.x, p.y+1);
|
||||
}
|
||||
|
||||
if( p.y > 0 && !lpp[-width] && dpp[-dstep] != newVal && std::abs(dp - dpp[-dstep]) <= maxDiff )
|
||||
{
|
||||
lpp[-width] = curlabel;
|
||||
*ws++ = Point2s(p.x, p.y-1);
|
||||
}
|
||||
|
||||
// pop most recent and propagate
|
||||
// NB: could try least recent, maybe better convergence
|
||||
p = *--ws;
|
||||
}
|
||||
|
||||
// assign label type
|
||||
if( count <= maxSpeckleSize ) // speckle region
|
||||
{
|
||||
rtype[ls[j]] = 1; // small region label
|
||||
ds[j] = (T)newVal;
|
||||
}
|
||||
else
|
||||
rtype[ls[j]] = 0; // large region label
|
||||
}
|
||||
rtype[ls[j]] = 0; // large region label
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
void cv::filterSpeckles( InputOutputArray _img, double _newval, int maxSpeckleSize,
|
||||
double _maxDiff, InputOutputArray __buf )
|
||||
{
|
||||
@ -1054,16 +1118,3 @@ void cv::validateDisparity( InputOutputArray _disp, InputArray _cost, int minDis
|
||||
}
|
||||
}
|
||||
|
||||
CvRect cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity,
|
||||
int numberOfDisparities, int SADWindowSize )
|
||||
{
|
||||
return (CvRect)cv::getValidDisparityROI( roi1, roi2, minDisparity,
|
||||
numberOfDisparities, SADWindowSize );
|
||||
}
|
||||
|
||||
void cvValidateDisparity( CvArr* _disp, const CvArr* _cost, int minDisparity,
|
||||
int numberOfDisparities, int disp12MaxDiff )
|
||||
{
|
||||
cv::Mat disp = cv::cvarrToMat(_disp), cost = cv::cvarrToMat(_cost);
|
||||
cv::validateDisparity( disp, cost, minDisparity, numberOfDisparities, disp12MaxDiff );
|
||||
}
|
||||
|
@ -66,8 +66,8 @@ int main(int argc, char** argv)
|
||||
bool no_display = false;
|
||||
float scale = 1.f;
|
||||
|
||||
StereoBM bm;
|
||||
StereoSGBM sgbm;
|
||||
Ptr<StereoMatcher> bm = createStereoBM(16,9);
|
||||
Ptr<StereoMatcher> sgbm = createStereoSGBM(0,16,3);
|
||||
StereoVar var;
|
||||
|
||||
for( int i = 1; i < argc; i++ )
|
||||
@ -220,32 +220,33 @@ int main(int argc, char** argv)
|
||||
|
||||
numberOfDisparities = numberOfDisparities > 0 ? numberOfDisparities : ((img_size.width/8) + 15) & -16;
|
||||
|
||||
bm.state->roi1 = roi1;
|
||||
bm.state->roi2 = roi2;
|
||||
bm.state->preFilterCap = 31;
|
||||
bm.state->SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 9;
|
||||
bm.state->minDisparity = 0;
|
||||
bm.state->numberOfDisparities = numberOfDisparities;
|
||||
bm.state->textureThreshold = 10;
|
||||
bm.state->uniquenessRatio = 15;
|
||||
bm.state->speckleWindowSize = 100;
|
||||
bm.state->speckleRange = 32;
|
||||
bm.state->disp12MaxDiff = 1;
|
||||
//bm->set("roi1", roi1);
|
||||
//bm->set("roi2", roi2);
|
||||
bm->set("preFilterCap", 31);
|
||||
bm->set("SADWindowSize", SADWindowSize > 0 ? SADWindowSize : 9);
|
||||
bm->set("minDisparity", 0);
|
||||
bm->set("numDisparities", numberOfDisparities);
|
||||
bm->set("textureThreshold", 10);
|
||||
bm->set("uniquenessRatio", 15);
|
||||
bm->set("speckleWindowSize", 100);
|
||||
bm->set("speckleRange", 32);
|
||||
bm->set("disp12MaxDiff", 1);
|
||||
|
||||
sgbm.preFilterCap = 63;
|
||||
sgbm.SADWindowSize = SADWindowSize > 0 ? SADWindowSize : 3;
|
||||
sgbm->set("preFilterCap", 63);
|
||||
int sgbmWinSize = SADWindowSize > 0 ? SADWindowSize : 3;
|
||||
sgbm->set("SADWindowSize", sgbmWinSize);
|
||||
|
||||
int cn = img1.channels();
|
||||
|
||||
sgbm.P1 = 8*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
|
||||
sgbm.P2 = 32*cn*sgbm.SADWindowSize*sgbm.SADWindowSize;
|
||||
sgbm.minDisparity = 0;
|
||||
sgbm.numberOfDisparities = numberOfDisparities;
|
||||
sgbm.uniquenessRatio = 10;
|
||||
sgbm.speckleWindowSize = bm.state->speckleWindowSize;
|
||||
sgbm.speckleRange = bm.state->speckleRange;
|
||||
sgbm.disp12MaxDiff = 1;
|
||||
sgbm.fullDP = alg == STEREO_HH;
|
||||
sgbm->set("P1", 8*cn*sgbmWinSize*sgbmWinSize);
|
||||
sgbm->set("P2", 32*cn*sgbmWinSize*sgbmWinSize);
|
||||
sgbm->set("minDisparity", 0);
|
||||
sgbm->set("numDisparities", numberOfDisparities);
|
||||
sgbm->set("uniquenessRatio", 10);
|
||||
sgbm->set("speckleWindowSize", 100);
|
||||
sgbm->set("speckleRange", 32);
|
||||
sgbm->set("disp12MaxDiff", 1);
|
||||
sgbm->set("fullDP", alg == STEREO_HH);
|
||||
|
||||
var.levels = 3; // ignored with USE_AUTO_PARAMS
|
||||
var.pyrScale = 0.5; // ignored with USE_AUTO_PARAMS
|
||||
@ -267,12 +268,12 @@ int main(int argc, char** argv)
|
||||
|
||||
int64 t = getTickCount();
|
||||
if( alg == STEREO_BM )
|
||||
bm(img1, img2, disp);
|
||||
bm->compute(img1, img2, disp);
|
||||
else if( alg == STEREO_VAR ) {
|
||||
var(img1, img2, disp);
|
||||
}
|
||||
else if( alg == STEREO_SGBM || alg == STEREO_HH )
|
||||
sgbm(img1, img2, disp);
|
||||
sgbm->compute(img1, img2, disp);
|
||||
t = getTickCount() - t;
|
||||
printf("Time elapsed: %fms\n", t*1000/getTickFrequency());
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user